Appfire

SeniorDataEngineer-DataInsights

$145–210k ~AI est. United States Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Data Engineer - Data Insights at Appfire. Skills: Data engineering, Cloud infrastructure, Data platform architecture. Own solution development lifecycle. Build Proof of Concepts”

What You'll Achieve.

Ensure stability and performance; Empower company-wide decision-making; Ensure accurate data ingestion; Ensure secure data availability

Industry & Context.

Problems you'll solve

Solve complex data puzzles; Resolve edge cases

What They're Looking For.

Must Have

5+ years data engineering role, 5+ years building data products, 5+ years advanced SQL, 5+ years complex ETL/ELT, 5+ years advanced Python, 5+ years AWS cloud environments, 5+ years Terraform, 5+ years Docker, 3+ years dbt

Nice to Have

Kubernetes experience a plus

What You'll Do.

Own solution development lifecycle

Build Proof of Concepts

Build Minimum Viable Products

Iterate production solutions

Stand up data delivery solutions

Optimize data delivery solutions

Manage data pipelines

Develop integration patterns

Develop custom data pipelines

Architect data solutions

Maintain data solutions

Maintain cloud infrastructure

Evolve custom data lake

Manage Fivetran operations

Manage custom pipeline operations

Implement data quality checks

Spearhead AI adoption

Automate Pull Requests

Enforce 'definition of done'

Accelerate test coverage

Accelerate release management

Integrate AI capabilities

Develop intelligent assistants

Develop intelligent agents

Drive proof-of-concepts

Implement PII management

Apply masking policies

Enforce row-level security

Enforce column-level security

Develop monitoring solutions

Deploy governance strategies

Champion best practices

Reduce technical debt

Provide technical mentorship

Provide soft-skill mentorship

How You'll Work.

Team & Collaboration

Internal partners; External partners; Business teams; Analytics teams; Engineering teams; Cross-departmental projects

Communication Scope

Translate technical architectures

Process & Methodology

Agile, Project leadership, Multitasking

Full Job Description

At Appfire, we believe that great work happens when people get to choose how they work. After 20 years of creating software that empowers teams to break silos and collaborate seamlessly, we've learned that one size does not fit all. We’re a team of 800+ employees, working remotely across 28 countries. Our flagship products include: Appfire Flow, JXL, Comala Document Management, 7Pace Time Tracker, Jira Misc Workflow Extensions, and BigPicture. Here you can read some of our customer stories: https://appfire.com/resources/resource-library/customer-stories About the role: Data is the fuel behind Appfire's global footprint. We’ve grown fast, and now our focus has shifted toward building the most mature, high-performing data platform in our industry. We are looking for a Senior Data Engineer to take ownership of our core infrastructure, champion engineering excellence, and help shape the future of our data ecosystem. Leveraging your expert Python, SQL, and cloud infrastructure skills, you will develop pragmatic architectures that ensure stability and performance across the organization. As a key member of our central data insights team, you will evolve our custom data lake ("firelake" built on AWS and Snowflake). To accelerate our platform optimization efforts, you will ruthlessly eliminate technical debt, resolve edge cases, and introduce modern, AI-driven development practices. This isn't just about maintaining pipelines; it's about architecting a highly secure, resilient, and scalable foundation that empowers company-wide decision-making. If you love solving complex data puzzles, driving overarching data strategy, and seeing the direct impact of your work across an entire organization, let's talk. What you’ll do: Data Delivery Solution Lifecycle Ownership: Own the complete solution development lifecycle, from driving initial requirements to building Proof of Concepts (POCs) and Minimum Viable Products (MVPs), and continuously iterating to improve and scale production

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